Implementasi Peraturan Daerah Nomor 9 Tahun 2011 Tentang Rencana Tata Ruang Wilayah Kabupaten Cilacap
Bibliographic record
Abstract
Peningkatan jumlah penduduk secara tidak langsung mempengaruhi jumlah kebutuhan terhadap tanah. Penggunaan dan perubahan lahan di Kabupaten Cilacap mengalami peningkatan seiring dengan pertambahan kebutuhan penduduk terhadap lahan. Penggunaan lahan sering kali terjadi untuk perumahan, pembangunan dan perkembangan ekonomi juga sarana prasarana. Dalam hal ini Pemerintah Daerah melalui Perda RTRW No. 9 Tahun 2011 tentang Rencana Tata Ruang Wilayah Kabupaten Cilacap, memiliki peran dalam mengatur dan mengendalikan penggunaan lahan pertanian dengan tujuan menekan fenomena alih fungsi lahan yang terjadi. Penelitian ini menggunakan metode kualitatif dengan pendekatan deskriptif. Dalam penelitian ini diperoleh hasil bahwa perkembangan alih fungsi lahan pertanian menjadi non pertanian masih kerap sekali terjadi dan Peraturan Daerah yang ada belum diterapkan secara efektif. Efektifitas instrumen implementasi pengendalian alih fungsi lahan masih belum berjalan secara optimal dan belum sesuai dengan rancangan dan tujuan Kabupaten Cilacap yang ada di dalam peraturan daerah. Population enhancement affects the amount of land needs indirectly. The use and change of land in Cilacap are increasing along with the needs. It happens almost for housing, constructing, economic, and infrastructure development. In this case, Local government in local regulation RTRW Number 9 of 2011 concerning the spatial plan of Cilacap district has a role in regulating and controlling the use of conversion in Cilacap with the target to suppress the phenomenon happened. This study used a qualitative method with a descriptive approach. In this study, the result showed the development of conversion still happened and the local regulation is not implemented effectively. Besides, the effectiveness of the instrument for controlling the conversion did not run optimally and not fit yet with the plan and purpose in local regulation of Cilacap.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.114 | 0.035 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".